Week 5 Assignments

Assignment 2

Business Forecasting

From your textbook, Statistics for Management and Economics, complete the following exercises:

 

“Time Series Analysis and Forecasting”: Exercises 20.47, 20.48, 20.49, 20.50, and 20.51

 

Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet. Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text box.

Name your Microsoft Excel workbook SU_MBA5008_W5_A2_LastName_FirstInitial.xls.

 

Cite any sources using the APA format on a separate page.

Exercises 20.47–20.51 are based on the following problem.

Xr20-47 The revenues (in $millions) of a chain of ice cream stores are listed for each quarter during the previous 5 years.

Year
Quarter	2009	2010	2011	2012	2013
1	16	14	17	18	21
2	25	27	31	29	30
3	31	32	40	45	52
4	24	23	27	24	32

20.47 Plot the time series.

20.48 Discuss why exponential smoothing is not recommended as a forecasting tool in this problem.

20.49 Use regression analysis to determine the trend line.

20.50 Determine the seasonal indexes.

20.51 Using the seasonal indexes and trend line, forecast revenues for the next four quarters.

Assignment 3

Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet. Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text box.

Name your Microsoft Excel workbook SU_MBA5008_W5_A3_LastName_FirstInitial.xls.

Cite any sources using the APA format on a separate page.

17.43

Perform the Durbin-Watson test at the 5% significance level to determine whether positive first-order autocorrelation exists when d = 1.10, n = 25, and k = 3.

Durbin–Watson statistic

You should have 2 answers for d. One will be for the subscript (1) and the other for the subscript (u)

17.46

Test the following hypotheses with α = .05.

H0: There is no first-order autocorrelation

H1: There is positive first-order autocorrelation

n = 50, k = 2, d = 1.38

Durbin–Watson statistic

20.19

Xr20-19 Plot the following time series to determine which of the trend models appears to fit better.

Period	1	2	3	4	5
Time Series	55	57	53	49	47
Period	6	7	8	9	10
Time Series	39	41	33	28	20

20.35

The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the 7 values for next week. ŷ = 120 + 2.3t t = 1, 2, … , 28

Day	Seasonal Index
Sunday	1.5
Monday	0.4
Tuesday	0.5
Wednesday	0.6
Thursday	0.7
Friday	1.4
Saturday	1.9

Per the instructor:

You will have to use the table provided in the question but you will have to expand the columns. Add additional columns for (t), the (y) formula shown, and your forecast. Plug in the values indicated and develop your answer

Assignment 4

Ongoing Data Exploration

In the Week 4 assignment, you were asked to build a multiple regression model to explain the variability in the median school year, using a minimum of seven independent variables. Using the same model, thoroughly assess your model's diagnostics. Identify all relevant assessment dimensions, briefly outline their purpose and importance, and provide an assessment of your model in terms of the identified diagnostic measures.

Submit your response in a 2- to 3-page Microsoft Word document

Name your document SU_MBA5008_W5_A4_LastName_FirstInitial.doc.

Cite any sources using the APA format on a separate page.